Scalable line-based wavelet image coding in wireless sensor networks

Stephan Rein, Martin Reisslein

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

Existing scalable wavelet image coding approaches, such as set partitioning in hierarchical trees and its derivatives, employ a memory-intensive tree-based coding structure. Existing tree-based wavelet coding approaches are therefore not suitable for memory-constrained sensor nodes. In this paper, we introduce a scalable wavelet image coding approach based on a line structure that requires very little memory. The proposed line-based approach is suitable for scalable wavelet image coding in memory-constrained sensor nodes, requiring only a few kilobytes of memory for a 256×256 pixel image. The presented line-based wavelet coding algorithm accesses the image data line by line and thus conforms with the data access patterns in current flash memory technology. Our performance evaluations demonstrate that the proposed scalable line-based image wavelet coding approach has no overhead compared to one-run (non-scalable) wavelet image coding and has competitive compression performance compared to JPEG 2000 and the recent Google WebP image format.

Original languageEnglish (US)
Pages (from-to)418-431
Number of pages14
JournalJournal of Visual Communication and Image Representation
Volume40
DOIs
StatePublished - Oct 1 2016

Fingerprint

Image coding
Wireless sensor networks
Data storage equipment
Sensor nodes
Flash memory
Pixels
Derivatives

Keywords

  • Low-memory image coding
  • Scalable image compression
  • Sensor node
  • Wavelet image coding

ASJC Scopus subject areas

  • Signal Processing
  • Media Technology
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

Cite this

Scalable line-based wavelet image coding in wireless sensor networks. / Rein, Stephan; Reisslein, Martin.

In: Journal of Visual Communication and Image Representation, Vol. 40, 01.10.2016, p. 418-431.

Research output: Contribution to journalArticle

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